E-Recycling Technology Innovators: Dr. Hamid Karbasi – Part 2

In this second and final part of my interview with Dr. Karbasi, Chair of the Industrial Research program in Advanced Recycling Technologies for WEEE at Conestoga College in Ontario, Canada, we cover where he sees advancements occurring for sensors used on scrap sorting airjet separators. These separators are used in many recycling applications such as municipal, electronics, metals, plastics, alternative fuel, and typically process a stream after shredding and size reduction. This research being funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada comes at a timely arrival as markets for recycled commodities encounter challenges. Sorting to higher grades and levels of purity can open up new sales channels for recovered materials and will be very helpful to recyclers worldwide. Please enjoy.

I know you also specialize in sensor sorting machines using different sensors coupled with airjets to perform many sorting tasks on shredded scrap. Where is your research focused on these type of machines?

There are several research areas for improving the software and hardware of sensor-based sorters. For instance, an intelligent software designed to sustain a high level of performance despite intake variations in terms of percentage, size, and condition of different fractions. This will avoid the need for retuning the machine parameters while the small variations in shredded scrap occur. It also requires improvement in hardware in order to provide feedback for the software to constantly measure the performance and tune the parameters accordingly. Furthermore, in order to assist the software to make informed and effective decisions, we need to collectively capture information regarding the color, composition, shape, and size of pieces. That is why approaches such as multi-sensing and sensor fusion are at the center of our attention for hardware upgrades.

What sensor technology is most promising, but not ready for commercialization yet?

We are evaluating several new technologies including hyper-spectrometer cameras in infrared (IR) wavelengths. Their high speed and accurate performance to differentiate plastics based on their polymer types, regardless of their coloration, is very promising. Our efforts are concentrated on how we can make the technology more affordable to be commercialized. Another very promising sensor technology is based on using a new Terahertz spectroscopy. This technology is in its infancy stage for sorting applications and we need to develop a Terahertz sensor array before integrating it into a machine for industrial application.

Plastics remain challenging to sort due to their varying chemistries and evolving composition such as bio-plastics, flame retardant and glass filled polymers, and painted plastics. How do you see sensor machines being able to manage these in an economical manner

Line-scan and hyper-spectral cameras in IR wavelengths have proven to be effective in identifying plastics but have their own shortcomings. For instance, their readings are very dependent upon surface conditions, as the technique is based on detecting the reflection of light from the surface of the plastic pieces. In order to detect the chemicals and additives properly, we need techniques that allow us the detection of internal structures. A new promising technology in Terahertz wavelength may be the solution. Terahertz wave is capable of transmitting through the bulk of materials such as plastics, and can provide valuable information about the internal chemistry. We have partnered with one local company who specializes in manufacturing Terahertz sensors to explore the possibility of sorting plastics using their technology.

What types of sorting tasks with these machines have you been most successful at?

Sorting based on the color of the pieces has been successfully completed. Our belt and slide-based sorters are capable of sorting with a high throughput and purity rate. They have been used by industry to separate plastics or white metals from circuit boards, wires, cables, and other colored metal contaminations.

Artificial intelligence is proliferating in many technical realms. When do you see it being applied and useful in recycling machinery?

We need to be aware that we live in an emerging era for the Internet of Things (IoT), where everything can be made smart and become connected to the internet for networking, monitoring, and remote control. IoT products such as our smart home thermostats, door locks, power outlets, cleaning and personal assistant robots, as a few examples, have been integrated into our daily lives and are all powered by AI. Good or bad, AI is growing to dominate our planet, from when you are filing your taxes to searching the internet. We have already witnessed a very sophisticated level of intelligence in robotics such as those humanoid robots developed by companies such as Honda and Boston Dynamics. Therefore, realizing a dismantler robot or a self-tuning smart sorter for our industry is not far from reality.

What project has been the most significant for you and your team?

All of our projects related either to sensor-based sorting or robotic dismantling and recycling have been very exciting and significant for our industry. They are novel projects formed by new and outside-of-the-box thinking. We have high hopes that they will result in very innovative solutions to assist the E-scrap industry for accessing very innovative technologies. Of course, these projects are in different stages of development. For instance, our sorting projects were transferred into a recycling plant in 2014 for further testing and verification, while prototypes are being developed for our robotic projects in the lab.

What areas might you focus on next besides robotics and airjet sorters?

Another research topic which recently grabbed my attention relates to modernizing E-scrap warehouses. For the sake of building my case, I would like to borrow the following introduction from an interesting article titled “AGVs Roll into a New Role: Equipped with new sensors and smart software, automatic guided vehicles are pursuing and eliminating non-value-added movement of goods in warehouses and DCs.”, published in January 2017 at Modern Materials Handling Magazine by Josh Bond:

“As the likes of Google and Apple pour resources into the development of driverless technology, the decreased price and improved performance of the vehicles are benefiting the makers of driverless industrial vehicles. Already, Amazon is poised to become one of the biggest users—and suppliers—of automatic guided vehicles in the warehousing and distribution space.

But AGVs aren’t just for those with big budgets and massive operations. In fact, AGVs aren’t even always AGVs. The “guided” part of that acronym, familiar from decades of autonomous vehicles designed to follow magnetic tapes, wires and other fixed paths, is now just one of a growing number of form factors. For the purposes of this story, AGV is an umbrella term including self-driving vehicles, autonomous mobile robots, vision-guided vehicles and more—some of which require no infrastructure to successfully navigate. As these vehicles become increasingly comfortable in dynamic, unstructured environments, these platforms have quickly migrated from manufacturing applications to warehousing supporting manufacturing to pure warehousing and distribution…”

I encourage the readers of this interview to read the full article on-line. But the point here is to think of how AGV technology can reduce costs and energy in E-scrap warehouses and add the flexibility they need. Perhaps, you agree with me that there is a high degree of dynamic environment and activities going on in such a plant. How great would it be to change the pathway configurations for material and product handling by a click of a button? How valuable is the traceability of materials and goods from the back of a truck to the back of a truck? These are the questions that we are trying to answer in this new research topic and understand how the technology can be customized and implemented to modernize E-scrap warehouses.

Conclusions

From hyperspectral to terahertz to other infrared bands of the electromagnetic wavelength, leading researchers and organizations see opportunity applying these new sensor approaches to commercial airjet sorters for recovery of various commodities from recycling sources. The research also looks at intelligent software development needed to take the richer amounts of data from new sensors and make sorting decisions. These researchers are not only focusing on inventing, but innovating and finding novel methods to lower costs to manufacture and make these technologies available and reasonable to as many recyclers as possible. Dr. Karbasi’s outlook on future technical opportunities for recycling plants involving guided autonomous systems entering the workflow and using real time data to guide activity is exciting and also needed to keep up with economic pressures on businesses in our sector. It has been an honor to speak with Dr. Karbasi about his fantastic work and journey and I thank him.

Our next interviews will turn towards industry veterans of recycling machinery companies covering various sectors about where they see latest recycling trends.